The application of computers in education has been limited by several problems, including a failure to provide systems that adapt or individualize to each student, a failure to integrate systems effectively into the existing classroom in elementary and secondary schools, and a failure to exploit technological developments. Although during the last three decades, a number of interactive educational techniques have been implemented on computers, all these systems lack the ability to recognize and to adapt to each student's individual characteristics. The common motivation for interactive educational techniques was the recognition that individual student interaction fosters learning to a greater degree than mere passive exposure to a fixed pace presentation (Kulik et al., 1986, Effectiveness of computer-based adult learning: a meta-analysis, Journal of educational computing research 2:235-252; Kulik et al., 1983, Effects of computer-based teaching on secondary school students, Journal of educational psychology 75:19-26). Existing, interactive educational techniques have many variants: programmed instruction, mastery learning, audio-tutorials, direct instruction, personalized system of instruction, precision teaching, fluency learning and others (Engleman et al., 1982, Theory of instruction: Principles and Applications, Irvington, New York; Keller, 1968, "Goodbye, teacher . . . ", Journal of Applied Behavior Analysis 1:79-89; Lindsley, 1990, Precision teaching: By teachers for children, Teaching Exceptional Children 22:353-359; West et al., 1992, Designs for Excellence in Education: the Legacy of B. F. Skinner, Sorris West, Inc., Longmont, Colo, pp. 147-160). Several systems have attempted to harness the interactivity of the computer for these interactive educational techniques. In early work, for example, text-based programmed instruction was converted to computer format and implemented on time-shared systems. This early development was extended with more sophisticated computer-assisted instruction ("CAI"), also known as compute based training ("CBT").
In CAI, for example, the computer acts as a teaching machine. A program presents instructional displays, accepts student responses, edits and judges those responses, branches on the basis of student responses, gives feedback to the student, and records and stores the student's progress. Examples of CAI systems include those of Carbonell, 1970, AI in CAI, an artificial intelligence approach to computer-assisted instruction, IEEE Transactions on Man-machine Systems, 11:190-202; Osin, 1984, CAI on a national scale, Proc. 4th Jerusalem Conf. on Information Technology, pp 418-424; Seidel 1971; Koffman et al., 1975, Artificial intelligence and artificial programming in CAI, Artificial Intelligence 6:215-234. Effective CAI instructional materials for a limited number of specific topics have been developed, as have special "authoring languages," which assist instructional developers on the tasks of designing instructional materials. U.S. Pat. No. 5,310,349 is exemplary of such CAI systems.
However, existing CAI systems do not adapt to their students. These systems merely sequence students through educational materials, based only on student performance during a current lesson and using only parameters such as recent responses and pre-requisite patterns. These systems do not gather or use information on more comprehensive student characteristics, such as past student performance, student performance on other courses, student learning styles, and student interests.
A greater deficiency is that existing CAI systems do not recognize characteristics of their individual students. They cannot be individualized or made responsive to their students styles. Thereby, these system ignore those roles of a human tutor that can be of unparalleled significance in the education of an individual. The human tutor assists in scheduling and prioritizing and in maintaining interest through proper reinforcement and knowledge of student abilities and preferences. A human tutor observes and addresses patterns of errors and maintains a consistent manner of interaction across a broad range of subject matters and activities. Moreover, a human tutor effectively integrates the cognitive, personal and social aspects of the instructional situation. In other words the human tutor provides a level of individualization based on student styles and on requirements of the instructional task. Furthermore, the human tutor provides an equally effective interaction with the teacher by accepting individualized instructions, collecting data and providing detailed reports. By failing to address these higher order services and roles of an effective human tutor, existing CAI systems fail to fully engage their students and thus fail instruct as well as possible.
Additionally, a further problem of computer assisted instruction, particularly in primary and secondary school settings is poor integration into the rest of the school curriculum and often poor quality of the educational materials. In application to elementary and secondary schools, two main patterns of instructional computer use prevail, which illustrate the compromises prevalent today. In one pattern, the integrated learning system ("ILS") is a dedicated installation that is used in schools to teach basic strands of reading, mathematics and related topics, spelling, writing, and other language arts, from grades one to six, or perhaps to eight or nine (EPIE, 1990, Integrated Instructional Systems: an Evaluation, Educational Products Information Exchange, Hampton Bays, N.Y.). The paradox with this pattern, regardless of the quality of the instruction offered by these systems, the work of students in ILSs bears little relation to what goes on in the classrooms in that very same topic. The fundamental reason is that the teacher cannot influence or respond meaningfully to variations in student progress or to relations between the CAI curriculum and the classroom text, materials and activities. This is the case even where the ILS installation produces reports in some detail as to each student's progress and standing.
The second pattern of computer use in schools is that of standalone short units on specific topics (TESS, 1996, Database of Educational Software Systems, Educational Products Information Exchange, Hampton Bays, N.Y.). These can be hypercard programs, simulations, or games, and are usually separate from the basic classroom curriculum. Though occasionally of excellent quality, the paradox here is that these products are usually chosen for enhancement, possible optional, and do not account for a major component of school related instruction. No records are kept or returned regarding student performance. These programs have not made a major contribution to school instruction.
Finally, computer assisted instruction systems have ignored or underutilized such important developments in computer technology over the past four years as agent-based system, client-server systems, and networking systems. Though now an active field with a wide spectrum of activities from research to commercial applications, application of agent-based systems in educational, instructional, and homework tasks has not been explored.- Software systems for intelligent agents have successfully applied in travel arrangements, email management, meeting scheduling, stock portfolio management, and gathering information from the Internet (Maes, 1994, Agents that reduce work and information overload, Communications of the ACM 37:30-40). In all these applications, software agents perform tasks on the user's behalf, receiving only general instructions from their user but then executing detailed tasks with considerable independence and initiative. In client-server systems, these agents can operate in the client, the server, or both.
Recently, adaptive and personalized agent based systems have begun to be developed. Systems with adaptive agents, agents which learn from experience, has made gains with new techniques continually identified. Adaptive agents have permitted new commercially viable adaptive systems implemented across networks. In these systems, an agent is a "go-between," mediating relations in a manner whose function is understood with details being left to the agent itself. The agent acts as a "stand-in" for its user, who is thus freed from direct manipulation of the network. In instructional applications, there is an unmet need for an agent who serves two users: the school system and the individual student. This is the well-known role of the teaching assistant/tutor. Maes, 1994, and others have extended the metaphor of agent to that of personal assistant, an agent who learns some important characteristics of its user, and adapts its behavior accordingly. Agents can learn by a mixture of methods: observation, receiving feedback from its user, receiving instructions from the user, and consulting other agents concerning "similar problems." To combine the important properties of competence, trust, and intimacy that a personal assistant should have, an agent should be in touch with relevant data, represent important facts in a reliable manner, and engage with its user in a personal and fundamentally sympathetic--at times playful--manner. Approaches to the creation of agents with personal characteristics have begun to be explored. In this work, relevant techniques are found in the tradition of film animators who, through the portrayal of emotions, gave their characters the illusion of life.
Moreover, computer assisted instructional systems have only haphazardly exploited the potential of client-server systems and networking technologies. Client-server architectures have emerged as the principal architecture of distributed computer systems. Client systems, running under sophisticated windowing operating systems, can support advanced object based software applications, including high speed graphics, animation and audio output. Servers can store gigabytes of data and programs at central or distributed locations at quite reasonable cost. Object oriented database systems have been developed to store structured data on servers.
Client systems, in a striking change from only several years ago, now virtually all have multimedia capabilities, including high quality graphics, sound, and at least limited video playback capability. Text-to-speech software is presently available for use with these systems, and speech recognition software is on brink of widespread commercial acceptability on low cost platforms. New authoring tools support graphical methods for generation of multimedia presentations and computer based instructional materials having corresponding sequencing logic.
Clients and servers can be linked remotely with increasing convenience and decreasing cost. The Internet has emerged as a means of providing an inexpensive means of connecting computers to provide effective communications and access to information and other resources such as software. Further Internet developments that made the Internet truly universal include the HTML and the HTTP protocols, which provide platform independent access to hyperlinked multimedia information, and the Java.TM. programming language, which provides platform independent software for Internet applications programming. Subsets of the Internet--intranets--have become an increasingly important means for disseminating information and enabling communication within constrained domains, such as a single school system or corporate enterprise.
Existing CAI systems have not addressed these functional deficiencies nor have they exploited the possibilities of existing technologies.
Citation of references hereinabove shall not be construed as an admission that such a reference is prior art to the present invention.